Cohort Analysis in Marketing

Modern business is impossible without using the Internet. It does not matter if you sell something or produce it. Consumers need information, and the easiest way to get it is to search the network. In addition, the effectiveness of using different channels of communication is not always easy to learn, but for the Internet it's quite easy to do. One of the popular and visual methods is considered to be a cohort analysis. Like other methodologies for investigating cause-effect relationships in consumer behavior, it requires the accumulation of statistical information. The Internet allows you to do this "unnoticed" for the performer. After all, almost every action of the visitor of the site is registered here - from the date of the first visit to the amount of time spent on each page.

Statistics in the service of marketers

It is unlikely that today there are still those specialists who interpret the word "marketing" as "advertising" and "sales." Of course, these are two important components of marketing activities. But the basis still lies in the study of consumer demand and behavior. And then everything is transformed into a search for opportunities to meet these needs.

And once we talked about studying and analyzing, then - statistics help us. Accurate accumulation of a database on the characteristics of customers allows us to thoroughly study the demand and use the results of the analysis as profitable as possible.

Most often, marketers use correlation and regression analysis; They are interested in descriptive and predictive methodologies for studying consumers. All this requires the allocation of some of the most representative (or interesting for business) groups of clients by some indications. It is this combination that offers us a cohort analysis.

Statistical analysis and commerce

In sales, it is necessary to clearly understand the cause-effect relationship in the actions of clients. Cohort analysis allows you to do this by grouping consumers on several grounds. The most common segment is a general characteristic (shopping, buying, etc.), combined with the date of the event. In statistics, it is customary to talk about a group of people (objects) exhibiting similar behavior and signs. A simple example of a cohort is visitors who first visited the store one week before the New Year. Having studied their behavior, it is possible to draw conclusions about the effectiveness of advertising and commercial efforts.

Analytics

To help marketers have long come the developers of Google. They offer a variety of services for studying e-commerce statistics. Now you can conduct a cohort analysis in Google Analytics. Previously, it had to be done through compulsory segmentation of the audience. It was quite laborious and inconvenient. However, now the cohort analysis is carried out automatically. The analyst can only adjust the report parameters according to his requirements.

The report data is displayed in the form of a timeline and a table. In the settings, you can change the four parameter groups that use the cohort analysis.

The type of cohort is a general characteristic that unites a specific group of site visitors. Size can be grouped by time: exact day, week, month. If you select the "week" option, for example, the report groups the first time visitors to the site for a given week into one cohort.

Then you can change the "indicator". Variability here refers to viewing pages, the duration of the session, the number of users, etc. And the last parameter is the "date range". Thanks to this function, the analyst has the opportunity to monitor the cohort's actions during the time period from the established starting point to the current date. When choosing a grouping by days, it should be remembered that cohorts will be formed in rows, and dynamics of visitors' behavior - in columns.

How to use the analysis results

Having studied the reports, you can track the frequency of customer returns to the site. A comparison of quantitative indicators with the layout of content on the pages of the site will provide an opportunity to understand what exactly interests and attracts customers.

For example, according to the analysis, a group of visitors is allocated, which returns to the site with "enviable constancy". Having raised the plan for placing advertising materials about holding some shares or presenting new items in the range at the time your pages were visited by these customers, it is possible to draw conclusions about what attracted the attention of potential customers. This information allows to increase the efficiency of the company. This is how cohort analysis is used in marketing. It gives an opportunity to even more purposefully and qualitatively distribute the advertising budget and create effective channels of communication.

What to look for

For the effective use of any statistical tool, preparatory work is necessary. After all, the correctly posed question in the problem guarantees its quick solution.

What do you need to do before using a cohort analysis? Ask yourself a few questions:

• Why is this kind of sales dynamics observed?
• What is the time period (for an advertising campaign, for example)?
• How do I determine the time of a mailing to receive a large response?

The advanced hypotheses will help to more clearly define the parameters of the cohort analysis.

Conclusion

Having become acquainted with the possibilities of the basic cohort analysis in Google Analytics and getting an idea of its functional features, the marketer is quite capable of not only increasing the traffic of the site, but also turning a potential client (casual visitor) into a consumer.

Forming individual reports will give a clear idea of the characteristics of the target audience, will help understand its reaction to your activity, regardless of whether you place an information article or promotional offer on the site . Any marketing effort should be economically viable. Cohort analysis, CLTV, Unit Economics - any methodology for studying consumer behavior is aimed at identifying the cost-benefit ratio and optimizing it.

But do not go too far. Daily monitoring will give an incorrect idea of the reasons for visiting the site of the company by consumers. It is a long-term observation of the representatives of one cohort that will allow to track and correctly interpret changes in the behavior of clients.